literature-review
affaan-m/everything-claude-code
Systematic literature-review workflow for academic, biomedical, and technical research with search planning, screening, synthesis, and citation verification.
What is literature-review?
A structured methodology for conducting narrative, scoping, systematic, or meta-analysis literature reviews. Use this skill to find, screen, synthesize, and cite academic or technical literature for research questions, background sections, or evidence synthesis across peer-reviewed papers, preprints, patents, and technical reports.
- Define searchable research questions using PICO (clinical) or domain-specific frameworks
- Plan reproducible search protocols across PubMed, arXiv, Semantic Scholar, and domain-specific databases
- Deduplicate sources by DOI, ID, title, and normalized metadata
- Screen sources in stages (title, abstract, full text) with explicit exclusion reasons
- Extract structured data using standardized tables with design, population, method, outcome, and limitations
- Synthesize evidence by theme with confidence levels (high, medium, low) rather than paper-by-paper summaries
How to install literature-review
npx skills add https://github.com/affaan-m/everything-claude-code --skill literature-reviewHow to use literature-review
- 1.Define your research question and convert it to a searchable format using PICO (clinical) or domain-specific terms
- 2.Decide on review type (narrative, scoping, systematic, or meta-analysis) based on rigor needs
- 3.Create a search protocol specifying databases, date range, languages, publication types, and inclusion/exclusion criteria
- 4.Execute searches across selected databases and log each query, filters, result count, and export format
- 5.Deduplicate results using DOI, PMID/arXiv ID, exact title, and normalized title plus author and year
- 6.Screen sources in stages: title, abstract, full text; record exclusion reasons for systematic work
- 7.Extract data into a structured table with study design, population, method, comparator, outcome, and limitations
- 8.Synthesize evidence by theme, grouping findings and assigning confidence levels rather than summarizing individually
Use cases
- Building a systematic review for a clinical intervention or biomedical research question
- Mapping the state of the art and identifying gaps for a technical or CS research domain
- Synthesizing conflicting evidence across multiple peer-reviewed sources for a background section
- Preparing citation-backed evidence for a research paper, grant proposal, or clinical guideline
- Comparing methodologies and benchmarks across technical papers and preprints
- Academic researchers conducting literature reviews for papers or theses
- Biomedical and clinical researchers preparing systematic or scoping reviews
- Technical and software researchers surveying methods and baselines
- Grant writers and proposal authors needing evidence synthesis
- Anyone synthesizing state-of-the-art knowledge for a specific research question
literature-review FAQ
Minimum set: PubMed (biomedical/life sciences), arXiv (CS, math, physics, preprints), and Semantic Scholar or Crossref (broad discovery). Add domain-specific sources like clinical-trial registries, patent databases, standards bodies, or official technical documentation as needed.
Default to scoping review for exploratory work and broad synthesis. Use systematic review for publication or clinical claims requiring reproducible protocol and explicit screening. Narrative review is useful for orientation. Meta-analysis adds quantitative effect aggregation to systematic review.
Include them if relevant, but clearly label them as preprints or non-peer-reviewed. Distinguish them from primary peer-reviewed evidence in your synthesis and do not claim the same rigor as peer-reviewed sources.
Do not omit negative or conflicting findings. Synthesize by theme and note methodological differences, population limits, or recency that may explain conflicts. Assign confidence levels (high, medium, low) based on evidence quality and replication.
Document your search protocol before collecting sources, keep a detailed search log with database, date, query, filters, and result count, record deduplication and exclusion decisions with reasons, and use structured extraction tables. This allows others to verify and replicate your work.
Full instructions (SKILL.md)
Source of truth, from affaan-m/everything-claude-code.
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. metadata: origin: community
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 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.
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