/literature-review

name: literature-review
description: Conducts systematic, scoping, and narrative literature reviews using PubMed, arXiv, bioRxiv, Semantic Scholar, and other appropriate sources. Use for research synthesis, reproducible literature searches, screening, citation checking, or preparing Markdown and PDF reviews. Tracks search coverage, records versus studies, and evidence limitations; supports meta-analysis planning but does not supply a meta-analysis engine.
allowed-tools: Read Write Edit Bash
license: MIT license
compatibility: Python 3.10+ with requests; network for DOI checks and searches. Optional parallel-cli requires Parallel authentication. PDF export needs Pandoc and XeLaTeX; AI schematics need OPENROUTER_API_KEY.
metadata:
  version: "1.11"
  last-reviewed: "2026-09-30"
  skill-author: K-Dense Inc.
  openclaw:
    primaryEnv: OPENROUTER_API_KEY
    envVars:
    - name: OPENROUTER_API_KEY
      required: false
      description: OpenRouter API key for the skill's LLM-powered steps.

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](https://www.prisma-statement.org/prisma-2020-flow-diagram) 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](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. **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 6. **Preserve all eligible records**: Citation counts can order exploratory reading but must not determine eligibility or replace risk-of-bias assessment 7. **Verify retrieved content**: Extraction can be incomplete; obtain the actual full report, or record it as not retrieved

Records, Reports, and Studies

1. **Deduplicate records, then link reports**: DOI/title deduplication removes repeated search hits; it does not identify every paper from the same study. Link preprints, journal articles, protocols, and follow-up reports using trial IDs, cohort descriptions, sites, and recruitment dates. 2. **Keep a study-to-report map**: Pre