Literature Review
Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and evidence logging. Use when the task is to find, screen, synthesize, and cite a body of academic or technical literature.
affaan-m on GitHub
Curated by PromptsEdge from a public repo · MIT license. All credit goes to the author.
What is this skill?
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
What’s inside
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 technical work, use:
- system or domain
- method or intervention
- comparison baseline
- evaluation metric
2. Plan the Search
Create a search protocol before collecting sources:
- databases to search
- date range
- languages
- publication types
- inclusion criteria
- exclusion criteria
- exact search strings
Minimum useful database set:
- PubMed for biomedical and life-sciences literature.
- arXiv for CS, math, physics, quantitative biology, and preprints.
- Semantic Scholar or Crossref for broad academic discovery.
- Domain-specific sources when relevant, such as clinical-trial registries, patent databases, standards bodies, or official technical docs.
3. Search and Log Evidence
Keep a search log that makes the review reproducible:
| Database | Date searched | Query | Filters | Results | Export |
| --- | --- | --- | --- | ---: | --- |
| PubMed | 2026-05-11 | `("CRISPR"[tiab] OR "Cas9"[tiab]) AND "sickle cell"[tiab]` | 2020:2026, English | 86 | PMID list |
| arXiv | 2026-05-11 | `CRISPR sickle cell gene editing` | q-bio, 2020:2026 | 9 | BibTeX |
Save raw IDs, URLs, DOIs, abstracts, and notes separately from the final prose.
4. Deduplicate
Deduplicate in this order:
- DOI
- PMID or arXiv ID
- exact title
- normalized title plus first author and year
Record how many duplicates were removed.
5. Screen Sources
Screen in stages:
- title
- abstract
- full text
For systematic work, record exclusion reasons:
- wrong population
- wrong intervention
- wrong outcome
- not primary research
- duplicate
- unavailable full text
- outside date range
6. Extract Data
Use a structured extraction table:
| Study | Design | Population/Data | Method | Comparator | Outcome | Key finding | Limitations |
| --- | --- | --- | --- | --- | --- | --- | --- |
| Author Year | RCT/cohort/review/etc. | sample or corpus | method | baseline | measured outcome | result | caveat |
For technical papers, include dataset, benchmark, metric, baseline, and reproducibility notes.
7. Synthesize
Group evidence by theme rather than summarizing papers one by one.
Useful synthesis lenses:
- strongest evidence
- conflicting evidence
- methodological weaknesses
- population or dataset limits
- recency and replication
- practical implications
- unanswered questions
Separate claims by confidence:
- High confidence: replicated, high-quality evidence across sources.
- Medium confidence: plausible but limited by sample, method, or recency.
- Low confidence: early, speculative, single-source, or weakly measured.
8. Verify Citations
Before finalizing:
- verify DOI, PMID, arXiv ID, or official URL
- check author names and publication year
- do not cite a paper for a claim it does not make
- mark preprints as preprints
- distinguish reviews from primary evidence
Output Template
# Literature Review: <Topic>
Generated: <date>
Review type: <narrative | scoping | systematic | meta-analysis>
Search window: <dates>
Databases: <list>
## Research Question
## Search Strategy
## Inclusion and Exclusion Criteria
## Evidence Summary
## Thematic Synthesis
## Gaps and Limitations
## References
## Search Log
Pitfalls
- Do not treat search snippets as evidence.
- Do not mix preprints, reviews, and primary studies without labeling them.
- Do not omit negative or conflicting findings.
- Do not claim systematic-review rigor without a reproducible protocol.
- Do not use a single database for a broad claim unless the scope is explicitly limited to that database.
Install this skill
- 1
Get the skill — it’s free
Use the Get this skill panel. Unlocked skills stay in My skills. - 2
Download or clone the files
Download the zip, or clone the repo and copy theskills/scientific-thinking-literature-reviewfolder. - 3
Put it where your agent looks for skills
For Claude Code, use your personal skills folder (every project) or a project’s own folder:~/.claude/skills/literature-review/SKILL.md # all projects .claude/skills/literature-review/SKILL.md # this project only
- 4
Just ask
No command needed. The agent reads the skill’s description and loads it on its own when your request matches.
SKILL.md frontmatter
What your agent reads to decide when to load this skill.
--- name: literature-review description: Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and evidence logging. Use when the task is to find, screen, synthesize, and cite a body of academic or technical literature. ---
Files
This skill lives in a public GitHub repo. Browse the files on GitHub ↗
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