
Literature Review
A structured framework for conducting academic literature reviews, from planning your search strategy through final synthesis. Walks you through the PICO framework for research questions, covers major databases like PubMed and Semantic Scholar with Boolean search patterns, and provides screening workflows with PRISMA diagrams. Includes citation format templates for APA, Nature, and Vancouver styles, plus quality assessment tools like Cochrane Risk of Bias. The thematic organization tables and comparison matrices are genuinely useful for keeping track of findings across dozens of papers. Best suited for systematic reviews where you need methodological rigor, though it works fine for narrative reviews too if you ignore the heavy process bits.
- skills.sh installs
- 343
- GitHub stars
- 7
- last updated
- Aug 21, 2026
Install
$ npx -y skills add eyadsibai/ltk --skill literature-review --agent claude-codeInstalls into .claude/skills of the current project.
Files
Literature Review Guide
Conduct comprehensive, systematic literature reviews using academic databases.
When to Use
- Conducting systematic literature reviews
- Synthesizing research on a topic
- Writing literature review sections
- Identifying research gaps
- Building bibliographies
Core Workflow
Phase 1: Planning
-
Define Research Question (PICO framework for clinical)
- Population, Intervention, Comparison, Outcome
-
Establish Scope
- Review type: narrative, systematic, scoping
- Time period, geographic scope
- Study types to include
-
Develop Search Strategy
- Key terms and synonyms
- Boolean operators (AND, OR, NOT)
- Database-specific syntax
Phase 2: Searching
Key Databases:
| Database | Coverage |
|---|---|
| PubMed | Biomedical, life sciences |
| arXiv | Physics, CS, math preprints |
| Semantic Scholar | Broad academic |
| Google Scholar | Broad coverage |
| Web of Science | Multidisciplinary |
Search Strategy Template:
(term1 OR synonym1) AND (term2 OR synonym2) AND (term3)
Sponsors
Details
- Repository
- github.com/eyadsibai/ltk
- Categories
- Git & Pull Requests, Code Review & Quality, Data Science & ML
- First seen
- Jun 3, 2026