# Literature Review > Conduct systematic literature reviews using a structured workflow. Use when starting a new research project, surveying a field, or documenting related work for a paper. Use when this capability is needed. - Skill: `tomevault-io/literature-review-4` (Agent Skill, multi-file: 2 files) - Install (CLI): `npx skillmds@latest add tomevault-io/literature-review-4` - Raw SKILL.md: https://api.skillmd.com/api/skills/tomevault-io/literature-review-4/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Research & Search - Author: tomevault-io (https://skillmd.com/u/tomevault-io) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/tomevault-io/literature-review-4 --- # Literature Review Systematic workflow for conducting comprehensive literature reviews. ## When to Use - Starting a new research project - Surveying a research field - Writing the Related Work section of a paper - Identifying research gaps - Building a comprehensive reading list ## PRISMA-Lite Workflow This workflow adapts the PRISMA (Preferred Reporting Items for Systematic Reviews) framework for ML/AI research. ### Phase 1: Define Scope Before searching, define: 1. **Research Question**: What are you trying to learn? 2. **Inclusion Criteria**: What makes a paper relevant? 3. **Exclusion Criteria**: What makes a paper not relevant? 4. **Time Frame**: How far back to search? 5. **Search Sources**: Which databases to use? Document in `literature_review.md`: ```markdown ## Review Scope ### Research Question [Your research question here] ### Inclusion Criteria - [ ] Criterion 1 - [ ] Criterion 2 ### Exclusion Criteria - [ ] Criterion 1 - [ ] Criterion 2 ### Time Frame [e.g., 2019-present] ### Sources - [ ] Semantic Scholar - [ ] arXiv - [ ] Google Scholar - [ ] ACL Anthology ``` ### Phase 2: Search Execute systematic search using paper-finder or manual search: 1. **Primary search**: Use core topic terms 2. **Secondary search**: Use method/technique names 3. **Citation search**: Check references of key papers Track search queries: ```markdown ## Search Log | Date | Query | Source | Results | Notes | |------|-------|--------|---------|-------| | YYYY-MM-DD | "query here" | Semantic Scholar | N papers | Initial search | ``` ### Phase 3: Screening Three-stage screening process: #### Stage 1: Title Screening - Review all titles - Quick relevance judgment - Mark: Include / Exclude / Maybe #### Stage 2: Abstract Screening - Read abstracts for Include/Maybe papers - Evaluate methodology and findings - Mark: Include / Exclude #### Stage 3: Full-Text Screening - Download and read full papers - Verify relevance and quality - Extract key information Track screening: ```markdown ## Screening Results | Paper | Title Screen | Abstract Screen | Full-Text | Notes | |-------|-------------|-----------------|-----------|-------| | Paper1 | Include | Include | Include | Key baseline | | Paper2 | Maybe | Exclude | - | Different task | ``` ### Phase 4: Data Extraction For each included paper, extract: 1. **Bibliographic**: Authors, year, venue 2. **Problem**: What problem is addressed? 3. **Method**: What approach is used? 4. **Data**: What datasets/benchmarks? 5. **Results**: Key findings 6. **Limitations**: Acknowledged weaknesses 7. **Relevance**: How relates to our work? Use the extraction template in `assets/review_template.md`. ### Phase 5: Synthesis Organize findings by theme: 1. **Identify themes**: Group related papers 2. **Compare approaches**: What are the differences? 3. **Find gaps**: What's missing? 4. **Position work**: Where does your work fit? ## Output Files ### literature_review.md Main document tracking the review: ```markdown # Literature Review: [Topic] ## Review Scope [Scope definition] ## Search Log [Search queries and results] ## Paper Summaries [Individual paper notes] ## Themes and Synthesis [Grouped findings] ## Research Gaps [Identified opportunities] ## Key Citations [Must-cite papers for your work] ``` ### papers/ directory Organize downloaded papers: ``` papers/ ├── must_read/ # Relevance 3, priority reading ├── should_read/ # Relevance 2 ├── reference/ # Background papers └── README.md # Index of all papers ``` ## Tools ### Reading Large PDFs Use the PDF chunker to split papers into smaller PDF files that can be read directly. This preserves all formatting perfectly (unlike text extraction which loses formatting). **Dependencies:** ```bash # Using uv (recommended): uv add pypdf # Or with pip: pip install pypdf ``` **How to run:** ```bash python .claude/skills/literature-review/scripts/pdf_chunker.py ``` Options: - `--pages-per-chunk N`: Number of pages per chunk (default: 1) - `--output-dir DIR`: Output directory (default: `/pages`) **Output:** - Creates PDF chunk files: `_chunk_001.pdf`, `_chunk_002.pdf`, etc. - Creates a manifest: `_manifest.txt` listing all chunks with page ranges **Integration with screening workflow:** 1. During Phase 3 (Full-Text Screening), run the chunker on papers that need detailed review 2. For abstract skimming: read only chunk 1 (page 1 or pages 1-3) 3. For deep reading: read ALL chunk PDFs sequentially, writing notes after each 4. Check the manifest to see how many chunks exist 5. IMPORTANT: Do not skip chunks - methodology and results are in later chunks ### Verify Citations After completing the review, verify all citations are valid: ```bash python .claude/skills/literature-review/scripts/verify_citations.py literature_review.md ``` ## Quality Checklist - [ ] Research question clearly defined - [ ] Inclusion/exclusion criteria documented - [ ] Multiple sources searched - [ ] Search queries logged - [ ] Screening decisions recorded - [ ] Key information extracted from all included papers - [ ] Papers organized by theme - [ ] Research gaps identified - [ ] Citations verified ## References See `references/` folder for: - `screening_guide.md`: Detailed screening criteria See `assets/` folder for: - `review_template.md`: Template for literature_review.md --- > Converted and distributed by [TomeVault](https://tomevault.io/claim/chicagohai) — claim your Tome and manage your conversions.