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.

Use discipline-appropriate bibliographic databases for the reproducible search, with parallel-web (parallel-cli search) for scoping and supplementary discovery. Ranked web results and extracted excerpts cannot establish exhaustive coverage or substitute for full-text assessment. Bundled scripts process normalized records, check DOI registration, and render documents; they do not run a complete systematic review automatically.

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

Figures and PRISMA reporting

For systematic reviews, use the appropriate PRISMA 2020 flow template and reconciled screening counts. Distinguish records, reports, and studies, including reports not retrieved and reasons for full-text exclusions. Use tables or deterministic plotting for exact numbers, effect estimates, and risk-of-bias results.

Conceptual schematics are optional. The bundled generator needs OPENROUTER_API_KEY and creates a PNG draft with up to two generation/review iterations:

python scripts/generate_schematic.py "Conceptual evidence map; labels from the reviewed extraction table" \
  -o figures/evidence_map.png --doc-type journal --iterations 2

Generation uses OpenRouter's POST /api/v1/images with google/gemini-3.1-flash-image; review uses POST /api/v1/chat/completions with google/gemini-3.7-flash. The output path must end in .png. Inspect labels, counts, arrows, and accessibility yourself: success means an image was saved, whereas quality_met, final_reviewed, and termination_reason in the review log describe the automated review. Neither proves scientific accuracy. A failed refinement preserves the previous draft. Check current model availability before running paid generation; do not fabricate study counts in an image prompt.

Core Workflow

A literature review runs in seven phases, documented in full with commands and templates in 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, and a full worked review is in references/example_workflow.md.

Best Practices

Search Strategy

1. Pilot the question: Optionally use parallel-cli search for scoping, then test database queries against known eligible reports
2. Choose complementary sources: Justify database and registry coverage for the question; no fixed number of databases guarantees completeness
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

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