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affaan-m/literature-review

affaan-m

literature-review

Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and evidence logging.

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v1.0Saved May 15, 2026

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

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:

  1. DOI
  2. PMID or arXiv ID
  3. exact title
  4. normalized title plus first author and year

Record how many duplicates were removed.

5. Screen Sources

Screen in stages:

  1. title
  2. abstract
  3. 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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Overall Score

88/100

Grade

A

Excellent

Safety

95

Quality

88

Clarity

85

Completeness

82

Summary

This skill guides users through a systematic workflow for conducting academic and technical literature reviews. It provides a structured methodology covering research question definition, search planning, source screening, data extraction, evidence synthesis, and citation verification across multiple review types (narrative, scoping, systematic, meta-analysis).

Detected Capabilities

literature database searchsource deduplicationstructured data extractionevidence synthesiscitation verificationsearch protocol documentation

Trigger Keywords

Phrases that MCP clients use to match this skill to user intent.

systematic literature reviewevidence synthesisresearch questionscoping reviewacademic researchstate of the artcitation verificationliterature mapping

Use Cases

  • Building a systematic review protocol for publication or clinical practice
  • Synthesizing state-of-the-art findings for a research question
  • Mapping evidence gaps and contradictions across peer-reviewed and preprint literature
  • Preparing evidence-backed background sections for academic papers
  • Comparing evidence from multiple sources (papers, patents, technical reports, clinical trials)

Quality Notes

  • Comprehensive coverage of review types with clear guidance on rigor levels
  • Structured workflow with well-ordered stages (define, plan, search, screen, extract, synthesize, verify)
  • Good examples of PICO framework and database-specific search syntax
  • Includes deduplication strategy with clear ordering (DOI, ID, title, normalized)
  • Strong emphasis on citation verification and distinguishing evidence types (primary vs. review vs. preprint)
  • Evidence extraction table template is practical and domain-agnostic
  • Synthesis lenses are concrete and actionable (strongest evidence, conflicting evidence, methodological weaknesses)
  • Pitfalls section explicitly warns against common errors (treating snippets as evidence, omitting negative findings, false rigor claims)
  • Output template is complete with all required sections
  • Search logging guidance ensures reproducibility
Model: claude-haiku-4-5-20251001Analyzed: May 15, 2026

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