# literature-review

> Conduct comprehensive, systematic literature reviews using multiple academic databases (PubMed, arXiv, bioRxiv, Semantic Scholar, etc.) with verified citations in multiple styles, producing professionally formatted markdown documents and PDFs.

**Use case**: Systematic literature search across multiple academic databases

**Canonical URL**: https://agentcookbooks.com/skills/literature-review/

**Topics**: claude-code, skills, science, scientific-writing

**Trigger phrases**: "do a literature review", "search the literature on", "find papers about", "systematic review of", "meta-analysis search"

**Source**: [K-Dense AI](https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/scientific-skills/literature-review)

**License**: MIT

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## What it does

`literature-review` is a Claude Code skill from K-Dense AI's [scientific-agent-skills repo](https://github.com/K-Dense-AI/scientific-agent-skills). It turns Claude into a systematic reviewer that queries multiple academic databases in parallel — PubMed, arXiv, bioRxiv, Semantic Scholar, and others — then synthesizes results into a professionally formatted markdown document or PDF with verified citations in the target style (APA, Nature, Vancouver, etc.).

A session produces a structured literature review document: an introduction framing the search scope, a methods section documenting search strings and inclusion/exclusion criteria, a synthesized findings narrative, and a formatted reference list. Citations are verified, not hallucinated.

## When to use it

Reach for it when:

- You're starting a research project and need to map the existing evidence base before writing
- You're writing the Introduction or Background section of a manuscript and need a sourced synthesis rather than a summary from memory
- You need a documented, reproducible search for a systematic review or meta-analysis

When *not* to reach for it:

- You already know the specific papers you need — use `paper-lookup` for direct DOI/PMID retrieval
- You only need a quick answer to a factual question — `research-lookup` or `parallel-web` is faster

## Install

Copy the `SKILL.md` from K-Dense AI's [literature-review folder](https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/scientific-skills/literature-review) into `.claude/skills/literature-review/` in your project.

Trigger phrases: "do a literature review", "search the literature on", "systematic review of".

## What a session looks like

A typical session has three phases:

1. **Search design.** Claude asks for the topic, PICO elements if applicable, and date range. It proposes search strings across databases and you approve or adjust.
2. **Multi-database retrieval.** Queries run in parallel; results are de-duplicated, filtered against inclusion criteria, and ranked by relevance.
3. **Synthesis document.** Claude drafts the review narrative, groups findings by theme or study type, and appends a formatted reference list. You receive a markdown file ready for further editing.

## Receipts

**Where it works well:**
- Established biomedical topics with strong PubMed coverage — retrieval is comprehensive and citation verification is reliable
- Generating the documented search methodology section required by systematic review journals

**Where it backfires:**
- Very recent preprints on fast-moving topics — database latency means the last 2–4 weeks of arXiv/bioRxiv may be incomplete
- Niche sub-fields where the relevant literature is in conference proceedings not indexed in the supported databases

**Pattern that works:** run the search first with broad terms, review the candidate list, then narrow with MeSH or field-specific vocabulary for the final synthesis pass.

## Source and attribution

Originally authored by [K-Dense Inc.](https://github.com/K-Dense-AI). The canonical SKILL.md lives in the [`literature-review` folder](https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/scientific-skills/literature-review) of their public scientific-agent-skills repository.

License: MIT. Install, adapt, and redistribute with attribution preserved.

This page documents the skill from a practitioner's perspective. For the formal spec and any updates, defer to the source repo.