literature-review
Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and evidence logging.
npx skills add mturac/everything-openai-codex --skill scientific-thinking-literature-review --agent codex
Same command for any agent — swap --agent for claude-code, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Literature Review Use this skill when the task is to find, screen, synthesize, and cite a body of academic or technical literature. ## When to Use - Building a systematic, scoping, or narrative literature review. - Synthesizing the state of the art for a research question. - Finding gaps, contradictions, or future-work directions. - Preparing citation-backed background sections for papers or reports. - Comparing evidence across peer-reviewed papers, preprints, patents, and technical reports. ## Review Types - **Narrative review**: broad synthesis; useful for orientation. - **Scoping review**: maps concepts, methods, and evidence gaps. - **Systematic review**: predefined protocol, reproducible search, explicit screening and exclusion. - **Meta-analysis**: systematic review plus quantitative effect aggregation. Ask the user which level of rigor is needed. If unspecified, default to a scoping review for exploratory work and a systematic review for publication or clinical claims. ## Workflow ### 1. Define the Question Convert the prompt into a searchable research question. For clinical or biomedical work, use PICO: - Population - Intervention or exposure - Comparator - Outcome For te
- When to Use
- Review Types
- Workflow
- 1. Define the Question
- 2. Plan the Search
- 3. Search and Log Evidence
- 4. Deduplicate
- 5. Screen Sources
- 6. Extract Data
- 7. Synthesize
- 8. Verify Citations
- Output Template
- Pitfalls
What does the literature-review skill do?
Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and evidence logging.
How do I install it?
Run `npx skills add mturac/everything-openai-codex --skill scientific-thinking-literature-review --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From mturac/everything-openai-codex, a repository with 84 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.