/literature-review

name: literature-review
description: 'Systematic literature review workflow: scope, search (arXiv, Semantic Scholar, Google Scholar), screen, extract, synthesize, and identify gaps. Triggers on: "literature review", "survey the literature", "related work", "systematic review", "synthesize the research", "find papers about", "research gap analysis".'
metadata:
  version: 1.0.1
  complements:
    [arxiv-search, research-critique, manuscript-review, manuscript-provenance]
  category: review
  tags: [academic, literature, synthesis, citations]
  difficulty: intermediate

Literature Review

Systematic discovery, extraction, and synthesis of academic research on a defined topic.

When to use this skill vs. others

| Need | Skill | | ----------------------------------------------------- | ---------------------------------- | | Survey a research area, synthesize multiple papers | **literature-review** (this skill) | | Critique a single paper's methodology and claims | research-critique | | Audit a manuscript's formatting, structure, citations | manuscript-review | | Verify a manuscript's numbers trace to code | manuscript-provenance | | Search arXiv for papers matching a query | arxiv-search (utility) |

Workflow

Phase 1: Scope Definition

Before searching, establish the review boundaries:

1. **Research question** — What specific question does the review answer? Vague topics produce vague reviews. "What techniques exist for X" is weaker than "How do methods for X compare on metric Y across domains Z?" 2. **Inclusion criteria** — Define what counts:

• Date range (e.g., 2020–present)
• Publication type (peer-reviewed, preprints, both)
• Domains/categories (e.g., cs.CL, cs.AI)
• Minimum relevance threshold

3. **Exclusion criteria** — Define what does not count:

• Tangentially related work
• Non-primary sources (blog posts, tutorials) unless explicitly included
• Duplicate or superseded versions

4. **Expected output** — What form should the review take? Narrative synthesis, tabular comparison, gap analysis, annotated bibliography, or related-work section?

Present the scope to the user for confirmation before proceeding.

Phase 2: Search & Discovery

Execute searches across available sources. Use multiple queries with varying specificity to avoid single-query blind spots.

**Primary source: arXiv (via arxiv-search utility)**

uv run --with arxiv python scripts/arxiv_search.py "QUERY" --max-results 30 --sort-by relevance

Vary queries systematically:

• Broad topic query: `"retrieval augmented generation"`
• Field-scoped query: `ti:retrieval AND abs:generation AND cat:cs.CL`
• Author-anchored query: `au:lewis AND abs:retrieval` (when key authors are known)
• Recency query: same terms with `--sort-by submitted`

**Secondary sources (via web search/fetch):**

• Semantic Scholar API: `https://api.semanticscholar.org/graph/v1/paper/search?query=QUERY&limit=20&fields=title,authors,abstract,year,citationCount,externalIds`
• Google Scholar (via web search): `site:scholar.google.com QUERY`
• Connected Papers (for citation graph exploration): `https://www.connectedpapers.com/search?q=QUERY`

**Snowball strategy:**

• Forward snowball: find papers that cite a key paper (Semantic Scholar citations endpoint)
• Backward snowball: follow the references of key papers
• Use citation count as a signal for influence, not quality

Phase 3: Screening & Filtering

For each discovered paper, apply the inclusion/exclusion criteria from Phase 1.

Produce a **screening table**:

| # | ID | Title | Authors | Year | Relevant? | Reason | | --- | ---------- | ----------- | ------------- | ---- | --------- | ------------------------------- | | 1 | 2301.07041 | Paper Title | Author et al. | 2023 | Yes | Directly addresses RQ | | 2 | 2302.12345 | Other Paper | Author B | 2023 | No | Tangential — focuses on X not Y |

Rules:

• Screen on title + abstract first. Read full paper only for borderline cases.
• When uncertain, include. It is cheaper to drop a paper later than to miss it.
• Track exclusion reasons — they inform the review's limitations section.
• Flag papers that appear in multiple search queries as likely high-relevance.

Phase 4: Data Extraction

For each included paper, extract a structured record:

- id: "2301.07041"
  title: "Paper Title"
  authors: ["Author One", "Author Two"]
  year: 2023
  venue: "NeurIPS 2023"
  research_question: "How does X affect Y?"
  methodology: "Controlled experiment with N=1000"
  key_findings:
    - "Finding 1 with quantitative result"
    - "Finding 2 with effect size"
  limitations: "Single-domain evaluation"
  relevance_to_rq: "Directly compares methods A and B on metric Y"
  citation_count: 142

Extraction discipline:

• Record what the paper demonstrates, not what it claims to demonstrate.
• Distinguish empirical findings (data-backed) from interpretive claims (author's framing).
• Note methodology details that enable cross-paper comparison (datasets, metrics, baselines).
• If the paper is available via `pdf_url`, read it for extraction. Do not extract from abstracts alone for included papers.

Phase 5: Synthesis

Transform extracted records into structured analysis. The synthesis method depends on the output format requested in Phase 1.

**Thematic synthesis** — Group papers by theme, approach, or finding:

• Identify recurring themes across papers
• Note where papers agree, disagree, or address different aspects
• Highlight methodological trends (what approaches are gaining/losing traction)

**Comparative synthesis** — Build comparison tables:

| Method | Paper(s) | Dataset | Metric | Result | Limitations | | -------- | -------- | ------- | ------ | --