# Literature Review

> Realiza revisiones bibliográficas sistemáticas y completas usando varias bases académicas (PubMed, arXiv, bioRxiv, Semantic Scholar). Genera markdown y PDF con citas verificadas en varios estilos (APA, Nature, Vancouver).

Fuente: https://skillsagentes.com/skills/k-dense-ai/scientific-agent-skills/literature-review
Markdown: https://skillsagentes.com/skills/k-dense-ai/scientific-agent-skills/literature-review.md

Repositorio: https://github.com/K-Dense-AI/scientific-agent-skills
Autor: K-Dense-AI
Licencia: MIT license
Actualizado: hace 15 días
Coste de contexto: 120 tok instalada, 3.2k tok al activarse, 33.2k tok con todos los archivos del bundle
Bundle: 12 archivos, 130 KB
Permisos que pide: read write edit bash

## Instalación

Un skill son archivos markdown: los mismos archivos valen para cualquier agente y lo único que cambia es el directorio de destino, es decir la bandera `--agent`. Añade `-g` para instalarlo en todos los proyectos de la máquina.

```bash
# Claude Code
npx -y skills add K-Dense-AI/scientific-agent-skills --skill literature-review --agent claude-code
# Cursor
npx -y skills add K-Dense-AI/scientific-agent-skills --skill literature-review --agent cursor
# Codex
npx -y skills add K-Dense-AI/scientific-agent-skills --skill literature-review --agent codex
# Gemini CLI
npx -y skills add K-Dense-AI/scientific-agent-skills --skill literature-review --agent gemini
# Windsurf
npx -y skills add K-Dense-AI/scientific-agent-skills --skill literature-review --agent windsurf
# Cline
npx -y skills add K-Dense-AI/scientific-agent-skills --skill literature-review --agent cline
```

## Qué hace

- Busca en múltiples bases de datos académicas (PubMed, arXiv, bioRxiv, Semantic Scholar) con parallel-cli search
- Ejecuta las siete fases de una revisión sistemática: planificación, búsqueda, cribado, extracción, síntesis, verificación y redacción
- Verifica todas las citas contra la fuente real con verify_citations.py
- Genera documentos markdown y PDF profesionales con bibliografía en APA, Nature, Vancouver, etc.
- Genera al menos un diagrama (p. ej. flujo PRISMA) con la skill scientific-schematics

## Cuándo usarla

- Hacer una revisión bibliográfica sistemática para publicación o tesis
- Sintetizar el conocimiento actual sobre un tema en varias fuentes
- Hacer un meta-análisis o scoping review
- Escribir la sección de revisión de literatura de un paper

## Qué la activa

- "Haz una revisión sistemática de literatura sobre este tema"
- "Sintetiza los estudios publicados sobre esta terapia"
- "Genera el diagrama PRISMA de mi revisión"
- "Verifica las citas de mi documento de revisión"

## Antes de instalar

- Necesita parallel-cli (con `parallel-cli auth`) para la búsqueda web, y pandoc/LaTeX (mactex o texlive-xetex) para generar el PDF.
- Necesita en el PATH: curl, python
- Variables de entorno: OPENROUTER_API_KEY
- makes network requests
- needs API credentials

## Archivos

- SKILL.md — 12 KB
- assets/review_template.md — 13 KB
- references/citation_styles.md — 6 KB
- references/core_workflow.md — 10 KB
- references/database_strategies.md — 15 KB
- references/example_workflow.md — 2 KB
- references/search_and_citation.md — 6 KB
- scripts/generate_pdf.py — 5 KB
- scripts/generate_schematic.py — 7 KB
- scripts/generate_schematic_ai.py — 38 KB
- scripts/search_databases.py — 9 KB
- scripts/verify_citations.py — 7 KB

## SKILL.md

Reproducido tal cual desde K-Dense-AI/scientific-agent-skills bajo MIT license. Esta sección es el documento original y está en inglés.

# 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 uses the **parallel-web skill** (`parallel-cli search`) as the primary web search tool for broad academic literature discovery, supplemented by specialized database access skills (gget, bioservices, datacommons-client). It 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

## Visual Enhancement with Scientific Schematics

**⚠️ MANDATORY: Every literature review MUST include at least 1-2 AI-generated figures using the scientific-schematics skill.**

This is not optional. Literature reviews without visual elements are incomplete. Before finalizing any document:
1. Generate at minimum ONE schematic or diagram (e.g., PRISMA flow diagram for systematic reviews)
2. Prefer 2-3 figures for comprehensive reviews (search strategy flowchart, thematic synthesis diagram, conceptual framework)

**How to generate figures:**
- Use the **scientific-schematics** skill to generate AI-powered publication-quality diagrams
- Simply describe your desired diagram in natural language
- Nano Banana Pro will automatically generate, review, and refine the schematic

**How to generate schematics:**
```bash
python scripts/generate_schematic.py "your diagram description" -o figures/output.png
```

The AI will automatically:
- Create publication-quality images with proper formatting
- Review and refine through multiple iterations
- Ensure accessibility (colorblind-friendly, high contrast)
- Save outputs in the figures/ directory

**When to add schematics:**
- PRISMA flow diagrams for systematic reviews
- Literature search strategy flowcharts
- Thematic synthesis diagrams
- Research gap visualization maps
- Citation network diagrams
- Conceptual framework illustrations
- Any complex concept that benefits from visualization

For detailed guidance on creating schematics, refer to the scientific-schematics skill documentation.

---

## Core Workflow

A literature review runs in seven phases, documented in full with commands and templates
in [references/core_workflow.md](references/core_workflow.md):

1. **Planning and scoping** — the question, inclusion and exclusion criteria, and scope.
2. **Systematic literature search** — multi-database searching with recorded queries.
3. **Screening and selection** — title/abstract then full-text screening with counts kept
   for the PRISMA flow.
4. **Data extraction and quality assessment** — structured extraction and risk-of-bias
   or quality appraisal.
5. **Synthesis and analysis** — thematic or quantitative synthesis across studies.
6. **Citation verification** — every citation checked against the actual source.
7. **Document generation** — assembling the review with a complete bibliography.

Record every search string and date as you go: a review that cannot reproduce its own
search is not systematic. Per-database search guidance and citation styles are in
[references/search_and_citation.md](references/search_and_citation.md), and a full worked
review is in [references/example_workflow.md](references/example_workflow.md).

## Best Practices

### Search Strategy
1. **Start with parallel-web**: Use `parallel-cli search` with academic domains for initial broad coverage before querying specialized databases
2. **Use multiple databases** (minimum 3): Ensures comprehensive coverage — parallel-web counts as one source
3. **Include preprint servers**: Captures latest unpublished findings
4. **Document everything**: Search strings, dates, result counts for reproducibility — save all parallel-cli output to `sources/`
5. **Test and refine**: Run pilot searches, review results, adjust search terms
6. **Sort by citations**: When available, sort search results by citation count to surface influential work first
7. **Use parallel-cli extract**: Fetch full content from promising URLs found during search to verify relevance before full-text screening

### Screening and Selection
1. **Use multiple databases** (minimum 3): Ensures comprehensive coverage
2. **Include preprint servers**: Captures latest unpublished findings
3. **Document everything**: Search strings, dates, result counts for reproducibility
4. **Test and refine**: Run pilot searches, review results, adjust search terms

### Screening and Selection
1. **Use clear criteria**: Document inclusion/exclusion criteria before screening
2. **Screen systematically**: Title → Abstract → Full text
3. **Document exclusions**: Record reasons for excluding studies
4. **Consider dual screening**: For systematic reviews, have two reviewers screen independently

### Synthesis
1. **Organize thematically**: Group by themes, NOT by individual studies
2. **Synthesize across studies**: Compare, contrast, identify patterns
3. **Be critical**: Evaluate quality and consistency of evidence
4. **Identify gaps**: Note what's missing or understudied

### Quality and Reproducibility
1. **Assess study quality**: Use appropriate quality assessment tools
2. **Verify all citations**: Run verify_citations.py script
3. **Document methodology**: Provide enough detail for others to reproduce
4. **Follow guidelines**: Use PRISMA for systematic reviews

### Writing
1. **Be objective**: Present evidence fairly, acknowledge limitations
2. **Be systematic**: Follow structured template
3. **Be specific**: Include numbers, statistics, effect sizes where available
4. **Be clear**: Use clear headings, logical flow, thematic organization

## Common Pitfalls to Avoid

1. **Single database search**: Misses relevant papers; always search multiple databases
2. **No search documentation**: Makes review irreproducible; document all searches
3. **Study-by-study summary**: Lacks synthesis; organize thematically instead
4. **Unverified citations**: Leads to errors; always run verify_citations.py
5. **Too broad search**: Yields thousands of irrelevant results; refine with specific terms
6. **Too narrow search**: Misses relevant papers; include synonyms and related terms
7. **Ignoring preprints**: Misses latest findings; include bioRxiv, medRxiv, arXiv
8. **No quality assessment**: Treats all evidence equally; assess and report quality
9. **Publication bias**: Only positive results published; note potential bias
10. **Outdated search**: Field evolves rapidly; clearly state search date

## Integration with Other Skills

This skill works seamlessly with other scientific skills:

### Web Search & Extraction (parallel-web skill — PRIMARY)
- **parallel-cli search**: Broad academic and general web search with domain filtering — use for initial scoping, finding papers, citation chaining, and supplementary searches
- **parallel-cli extract**: Fetch full content from paper URLs, journal websites, and preprint servers — use for reading abstracts, extracting reference lists, and verifying paper details
- **parallel-cli search --include-domains**: Academic-focused search across scholarly domains (arxiv.org, pubmed, nature.com, etc.)

### Database Access Skills
- **gget**: PubMed, bioRxiv, COSMIC, AlphaFold, Ensembl, UniProt
- **bioservices**: ChEMBL, KEGG, Reactome, UniProt, PubChem
- **datacommons-client**: Demographics, economics, health statistics

### Analysis Skills
- **pydeseq2**: RNA-seq differential expression (for methods sections)
- **scanpy**: Single-cell analysis (for methods sections)
- **anndata**: Single-cell data (for methods sections)
- **biopython**: Sequence analysis (for background sections)

### Visualization Skills
- **matplotlib**: Generate figures and plots for review
- **seaborn**: Statistical visualizations

### Writing Skills
- **brand-guidelines**: Apply institutional branding to PDF
- **internal-comms**: Adapt review for different audiences
- **venue-templates**: Access venue-specific writing style guides when preparing reviews for publication

### Venue-Specific Writing Styles

When preparing a literature review for a specific journal, consult the **venue-templates** skill for writing style guidance:
- `venue_writing_styles.md`: Master style comparison across venues
- `nature_science_style.md`: Nature/Science flowing abstract style, story-driven structure
- `cell_press_style.md`: Cell Press graphical abstracts, Highlights format
- `medical_journal_styles.md`: NEJM/Lancet/JAMA structured abstracts, PRISMA compliance

These guides help adapt your review's tone, abstract format, and structure to match the target venue's expectations.

## Resources

### Bundled Resources

**Scripts:**
- `scripts/verify_citations.py`: Verify DOIs and generate formatted citations
- `scripts/generate_pdf.py`: Convert markdown to professional PDF
- `scripts/search_databases.py`: Process, deduplicate, and format search results

**References:**
- `references/citation_styles.md`: Detailed citation formatting guide (APA, Nature, Vancouver, Chicago, IEEE)
- `references/database_strategies.md`: Comprehensive database search strategies

**Assets:**
- `assets/review_template.md`: Complete literature review template with all sections

### External Resources

**Guidelines:**
- PRISMA (Systematic Reviews): http://www.prisma-statement.org/
- Cochrane Handbook: https://training.cochrane.org/handbook
- AMSTAR 2 (Review Quality): https://amstar.ca/

**Tools:**
- MeSH Browser: https://meshb.nlm.nih.gov/search
- PubMed Advanced Search: https://pubmed.ncbi.nlm.nih.gov/advanced/
- Boolean Search Guide: https://www.ncbi.nlm.nih.gov/books/NBK3827/

**Citation Styles:**
- APA Style: https://apastyle.apa.org/
- Nature Portfolio: https://www.nature.com/nature-portfolio/editorial-policies/reporting-standards
- NLM/Vancouver: https://www.nlm.nih.gov/bsd/uniform_requirements.html

## Dependencies

### Required CLI Tools
```bash
# parallel-cli (PRIMARY — for web search and URL extraction)
curl -fsSL https://parallel.ai/install.sh | bash
# Or: uv tool install "parallel-web-tools[cli]"
# Authenticate: parallel-cli auth
```

### Required Python Packages
```bash
uv pip install requests  # For citation verification
```

### Required System Tools
```bash
# For PDF generation
brew install pandoc  # macOS
apt-get install pandoc  # Linux

# For LaTeX (PDF generation)
brew install --cask mactex  # macOS
apt-get install texlive-xetex  # Linux
```

Check dependencies:
```bash
python scripts/generate_pdf.py --check-deps
```

## Summary

This literature-review skill provides:

1. **Systematic methodology** following academic best practices
2. **Parallel-web powered search** using `parallel-cli search` for fast, broad academic literature discovery with scholarly domain filtering
3. **Multi-database integration** via existing scientific skills (gget, bioservices, datacommons-client)
4. **Citation verification** ensuring accuracy and credibility
5. **Professional output** in markdown and PDF formats
6. **Comprehensive guidance** covering the entire review process
7. **Quality assurance** with verification and validation tools
8. **Reproducibility** through detailed documentation requirements

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

## Dónde encaja

- Categoría: [Investigación](https://skillsagentes.com/categorias/investigacion.md) — Investigación estructurada, búsqueda de fuentes y síntesis.
- Creador: [K-Dense-AI](https://skillsagentes.com/creators/k-dense-ai.md) — 163 skills en el directorio
- [Todas las skills](https://skillsagentes.com/skills.md)
- [Ranking de instalaciones](https://skillsagentes.com/ranking.md)

## Otras skills del mismo repositorio

- [Citation Management](https://skillsagentes.com/skills/k-dense-ai/scientific-agent-skills/citation-management.md): Gestión integral de citas académicas: busca en OpenAlex, PubMed y Google Scholar, extrae metadatos precisos, valida citas y genera entradas BibTeX correctamente formateadas.
- [Scientific Slides](https://skillsagentes.com/skills/k-dense-ai/scientific-agent-skills/scientific-slides.md): Crea decks de diapositivas y presentaciones para charlas de investigación: PowerPoint, presentaciones de conferencia, seminarios, defensas de tesis. Da estructura, plantillas, guía de tiempos y validación visual.
- [Infographics](https://skillsagentes.com/skills/k-dense-ai/scientific-agent-skills/infographics.md): Crea infografías profesionales con Nano Banana Pro AI y refinamiento iterativo inteligente. Usa Gemini 3.6 Flash para revisar la calidad e integra investigación con Perplexity Sonar. Soporta 10 tipos, 8 estilos y paletas para daltonismo.
- [Latex Posters](https://skillsagentes.com/skills/k-dense-ai/scientific-agent-skills/latex-posters.md): Crea pósteres de investigación profesionales en LaTeX con beamerposter, tikzposter o baposter, para conferencias y comunicación científica: layout, colores, columnas múltiples e integración de figuras.
- [Scientific Schematics](https://skillsagentes.com/skills/k-dense-ai/scientific-agent-skills/scientific-schematics.md): Crea diagramas científicos de calidad de publicación con la IA Nano Banana 2 y refinamiento iterativo inteligente. Gemini 3.6 Flash revisa la calidad y solo regenera si está por debajo del umbral de tu tipo de documento.

---

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